Prediction-based Routing with Packet Scheduling under Temporal Constraint in Delay Tolerant Networks

is a challenging problem due to the intermittent connectivity between the nodes. Researchers have proposed many routing protocols that adapt to the temporary connections of DTNs. One classification of routing protocols makes use of historical information to predict future contact patterns for any pair of nodes. However, most existing protocols focus on the probability of a path from the source to the destination without considering the information in a packet which includes the source, destination, size, TTL (Time-To-Live) and limited resources such as available buffer size and bandwidth. In this paper, we propose a new prediction-based routing algorithm that takes into account packet information under the conditions of limited transmission opportunities. The goal of this protocol is to increase the overall delivery ratio through scheduling packets at each node. Meanwhile, this protocol may sacrifice some messages ’ delivery delay time to some extent. Extensive simulation results with real traces show that our protocol with packet scheduling has better performance than the pure probabilistic routing algorithms in term of delivery ratio. Our protocol’s performance advantage is more obvious for nodes with higher packet intensity and shorter TTL in packets. I

NeuronBank: A Tool for Cataloging Neuronal Circuitry

The basic unit of any nervous system is the neuron. Therefore, understanding the operation of nervous systems ultimately requires an inventory of their constituent neurons and synaptic connectivity, which form neural circuits. The presence of uniquely identifiable neurons or classes of neurons in many invertebrates has facilitated the construction of cellular-level connectivity diagrams that can be generalized across individuals within a species. Homologous neurons can also be recognized across species. Here we describe NeuronBank.org, a web-based tool that we are developing for cataloging, searching, and analyzing neuronal circuitry within and across species. Information from a single species is represented in an individual branch of NeuronBank. Users can search within a branch or perform queries across branches to look for similarities in neuronal circuits across species. The branches allow for an extensible ontology so that additional characteristics can be added as knowledge grows. Each entry in NeuronBank generates a unique accession ID, allowing it to be easily cited. There is also an automatic link to a Wiki page allowing an encyclopedic explanation of the entry. All of the 44 previously published neurons plus one previously unpublished neuron from the mollusc, Tritonia diomedea, have been entered into a branch of NeuronBank as have 4 previously published neurons from the mollusc, Melibe leonina. The ability to organize information about neuronal circuits will make this information more accessible, ultimately aiding research on these important models

Oracle Eight

xv, 334 p. ; 24 cm

Oracle Eight

xv, 334 p. ; 24 cm

Indefinite and maybe information in deductive relational databases

In this dissertation, we present an extended relational model to represent indefinite and maybe kinds of incomplete information. A data structure, called an I-table, is defined which is capable of representing indefinite and maybe information. The information content of an I-table is precisely defined and some properties of I-tables are characterized. Redundancy in I-tables is discussed and an operator to remove it is presented. The relational algebra is then suitably extended to operate on I-tables. A correctness criterion is presented and the extended relational algebraic operations are shown to satisfy the correctness criterion. Queries are answered in the same way as with the regular relational algebra, however we may now expect indefinite and maybe answers to queries. The extended relational algebra is then used to implement a subclass of indefinite deductive databases. A special class of non-Horn rules, called I-rules, is defined. An additional operator, called project-union, which is a further extension to the extended projection operator is presented. The project-union operator is used to evaluate I-rules. The correctness of the algebraic approach to indefinite e deductive databases is established. Finally, we present generalized I-tables, called M-tables, which are capable of representing more general forms of indefinite information. The relational algebra is further generalized to operate on M-tables. Additional operators, R-projection and merge, are defined to answer queries about M-tables.</p